offset = round(offset*img.shape[0]) # convert to pixels dims = (img.shape[0]+offset, img.shape[1], img.shape[2]) g = m.makeCarrier(dims, T) print 'computing gratings...' L = 0.04 # learning rate niter = 501 # of iterations for i in range(niter): if i % 25 == 0: print "iteration [%4d/%4d]" % (i, niter) # update grating err = (1-img)/2 - (g[0:-offset,:,:] - g[offset:,:,:]) g[0:-offset,:,:] += L*err g[offset:,:,:] -= L*err g = m.smoothenPhase(g, 1e-4/T) print 'saving image...' g = m.makeGrating(g) # visualize gratings m.show(g, 312, 'grating') # visualize superpositions e = m.ones((offset, img.shape[1], img.shape[2])) s = m.vstack((e, g))*m.vstack((g, e)) m.show(s, 313, 'superposition') fig.savefig('./results/moire3.png', dpi=300)
Simple moire with a single color image """ import moirelib as m T = 1./40 # grating period print 'pre-processing images...' img = m.prepImage('audrey', mag=2, sigma=(0,T/4., 0)) fig = m.figure(figsize=(8,10)) m.show(img, 311, 'original') print 'generating gratings...' carrier = m.makeCarrier(img.shape, T) g1 = carrier-(1-img)/4 g2 = carrier+(1-img)/4 print 'smoothing phase...' g1 = m.smoothenPhase(g1, 1e-3/T, 50) g2 = m.smoothenPhase(g2, 1e-3/T, 50) print 'saving images...' g1 = m.makeGrating(g1) g2 = m.makeGrating(g2) m.show(g1,323, 'grating 1') m.show(g2,324, 'grating 2') m.show(g1*g2, 313, 'superposition') fig.savefig('./results/moire1.png', dpi=300)
""" Simple moire with a single color image """ import moirelib as m T = 1. / 40 # grating period print 'pre-processing images...' img = m.prepImage('audrey', mag=2, sigma=(0, T / 4., 0)) fig = m.figure(figsize=(8, 10)) m.show(img, 311, 'original') print 'generating gratings...' carrier = m.makeCarrier(img.shape, T) g1 = carrier - (1 - img) / 4 g2 = carrier + (1 - img) / 4 print 'smoothing phase...' g1 = m.smoothenPhase(g1, 1e-3 / T, 50) g2 = m.smoothenPhase(g2, 1e-3 / T, 50) print 'saving images...' g1 = m.makeGrating(g1) g2 = m.makeGrating(g2) m.show(g1, 323, 'grating 1') m.show(g2, 324, 'grating 2') m.show(g1 * g2, 313, 'superposition') fig.savefig('./results/moire1.png', dpi=300)
offset = round(offset * img.shape[0]) # convert to pixels dims = (img.shape[0] + offset, img.shape[1], img.shape[2]) g = m.makeCarrier(dims, T) print 'computing gratings...' L = 0.04 # learning rate niter = 501 # of iterations for i in range(niter): if i % 25 == 0: print "iteration [%4d/%4d]" % (i, niter) # update grating err = (1 - img) / 2 - (g[0:-offset, :, :] - g[offset:, :, :]) g[0:-offset, :, :] += L * err g[offset:, :, :] -= L * err g = m.smoothenPhase(g, 1e-4 / T) print 'saving image...' g = m.makeGrating(g) # visualize gratings m.show(g, 312, 'grating') # visualize superpositions e = m.ones((offset, img.shape[1], img.shape[2])) s = m.vstack((e, g)) * m.vstack((g, e)) m.show(s, 313, 'superposition') fig.savefig('./results/moire3.png', dpi=300)